Triple
T37372587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dibang Wildlife Sanctuary |
E927880
|
entity |
| Predicate | nearbyHumanSettlement |
P138521
|
FINISHED |
| Object | Anini |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Anini | Statement: [Dibang Wildlife Sanctuary, nearbyHumanSettlement, Anini]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyHumanSettlement Context triple: [Dibang Wildlife Sanctuary, nearbyHumanSettlement, Anini]
-
A.
nearbySettlements
chosen
Indicates that one settlement is located close to another settlement in geographic space.
-
B.
nearbySettlementRegion
Indicates that a settlement is located close to or within the surrounding area of a specified region.
-
C.
nearbySettlementGR
Indicates that one settlement is geographically located close to another settlement.
-
D.
nearbySettlementUS
Indicates that one settlement is geographically close to another settlement within the United States.
-
E.
hasNearestLargerSettlement
Indicates that one settlement is associated with the geographically closest settlement that is larger in size or population.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76eb820248190a5c395ca50ad002a |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff1ba8694481909ceb36f26ca85612 |
completed | May 9, 2026, 11:34 a.m. |
| PD | Predicate disambiguation | batch_69ff1b27f0f08190a9e74308c5b3d1ba |
completed | May 9, 2026, 11:31 a.m. |
Created at: May 3, 2026, 4:16 p.m.